High-sensitivity troponin T, NT-proBNP and glomerular filtration rate: A multimarker strategy for risk stratification in chronic heart failure

Alberto Aimo; James L. Januzzi; Giuseppe Vergaro; Andrea Ripoli; Roberto Latini; Serge Masson; Michela Magnoli; Inder S. Anand; Jay N. Cohn; Luigi Tavazzi; Gianni Tognoni; Jørgen Gravning; Thor Ueland; Ståle H. Nymo; Hans Peter Brunner La Rocca; Antoni Bayes-Genis; Josep Lupón; Rudolf A. de Boer; Akiomi Yoshihisa; Yasuchika Takeishi; Michael Egstrup; Ida Gustafsson; Hanna K. Gaggin; Kai M. Eggers; Kurt Huber; Ioannis Tentzeris; W. H. Wilson Tang; Justin L. Grodin; Claudio Passino; Michele Emdin

doi:10.1016/j.ijcard.2018.10.079

High-sensitivity troponin T, NT-proBNP and glomerular filtration rate: A multimarker strategy for risk stratification in chronic heart failure

Alberto Aimo, James L. Januzzi, Giuseppe Vergaro, Andrea Ripoli, Roberto Latini, Serge Masson, Michela Magnoli, Inder S. Anand, Jay N. Cohn, Luigi Tavazzi, Gianni Tognoni, Jørgen Gravning, Thor Ueland, Ståle H. Nymo, Hans Peter Brunner La Rocca, Antoni Bayes-Genis, Josep Lupón, Rudolf A. de Boer, Akiomi Yoshihisa, Yasuchika TakeishiMichael Egstrup, Ida Gustafsson, Hanna K. Gaggin, Kai M. Eggers, Kurt Huber, Ioannis Tentzeris, W. H. Wilson Tang, Justin L. Grodin, Claudio Passino, Michele Emdin

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

BACKGROUND: In a recent individual patient data meta-analysis, high-sensitivity troponin T (hs-TnT) emerged as robust predictor of prognosis in stable chronic heart failure (HF). In the same population, we compared the relative predictive performances of hs-TnT, N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP), hs-C-reactive protein (hs-CRP), and estimated glomerular filtration rate (eGFR) for prognosis.

METHODS AND RESULTS: 9289 patients (66 ± 12 years, 77% men, 85% LVEF <40%, 60% ischemic HF) were evaluated over a 2.4-year median follow-up. Median eGFR was 58 mL/min/1.73 m 2 (interquartile interval 46-70; n = 9220), hs-TnT 16 ng/L (8-20; n = 9289), NT-proBNP 1067 ng/L (433-2470; n = 8845), and hs-CRP 3.3 mg/L (1.4-7.8; n = 7083). In a model including all 3 biomarkers, only hs-TnT and NT-proBNP were independent predictors of all-cause and cardiovascular mortality and cardiovascular hospitalization. hs-TnT was a stronger predictor than NT-proBNP: for example, the risk for all-cause death increased by 54% per doubling of hs-TnT vs. 24% per doubling of NT-proBNP. eGFR showed independent prognostic value from both hs-TnT and NT-proBNP. The best hs-TnT and NT-proBNP cut-offs for the prediction of all-cause death increased progressively with declining renal function (eGFR ≥ 90: hs-TnT 13 ng/L and NT-proBNP 825 ng/L; eGFR < 30: hs-TnT 40 ng/L and NT-proBNP 4608 ng/L). Patient categorization according to these cut-offs effectively stratified patient prognosis across all eGFR classes.

CONCLUSIONS: hs-TnT conveys independent prognostic information from NT-proBNP, while hs-CRP does not. Concomitant assessment of eGFR may further refine risk stratification. Patient classification according to hs-TnT and NT-proBNP cut-offs specific for the eGFR classes holds prognostic significance.

Original language	English (US)
Pages (from-to)	166-172
Number of pages	7
Journal	International Journal of Cardiology
Volume	277
DOIs	https://doi.org/10.1016/j.ijcard.2018.10.079
State	Published - Feb 15 2019

Bibliographical note

Funding Information:
Dr. Januzzi has received grant support from Siemens, Singulex, and Prevencio; consulting income from Roche Diagnostics, Critical Diagnostics, Philips, and Novartis; and participates in clinical end point committees for Novartis, Amgen, Janssen, and Boehringer Ingelheim. Dr. Latini and Dr. Masson have received grant support and travel reimbursements from Roche Diagnostics. Dr. Tavazzi reports personal fees from Servier, personal fees from CVIE Therapeutics, outside the submitted work. Dr. Gravning reports lecture fees from AstraZeneca, Siemens and Abbott Laboratories, outside the submitted work. Dr. Brunner-La Rocca reports unrestricted research grants and consulting fees from Roche Diagnostics, as well as unrestricted research grants from Novartis and Vifor outside this work. Dr. Bayes-Genis has received grant support from Roche Diagnosis, lecture honoraria from Roche Diagnostics and Critical Diagnostics, and consulting income from Roche Diagnostics, Critical Diagnostics, and Novartis. Dr. Lup?n has received lecture honoraria from Roche Diagnostics. Dr. de Boer reports that Roche, Novartis, and AstraZeneca offered consultancy to UMCG; he also reports grants from AstraZeneca, grants from Bristol Myers Squibb, and grants from Trevena, outside the submitted work. Dr. Gustafsson reports personal fees from Boehringer-Ingelheim, personal fees from Novo Nordisk, personal fees from Novartis, personal fees from MSD, personal fees from Astra-Zeneca, outside the submitted work. Dr. Gaggin has received grant support from Roche and Portola; consulting income from Roche Diagnostics, Amgen and Ortho Clinical; research payments for clinical endpoint committees for EchoSense and Radiometer. Dr. Eggers has received honoraria from Abbott Laboratories and AstraZeneca, and has served as a consultant for Abbott Laboratories and Fiomi Diagnostics. Dr. Tang reports grants from National Institutes of Health, outside the submitted work. All disclosed relationships are modest. All other Authors have nothing to disclose.

Funding Information:
Dr. Januzzi has received grant support from Siemens , Singulex , and Prevencio ; consulting income from Roche Diagnostics, Critical Diagnostics, Philips, and Novartis; and participates in clinical end point committees for Novartis, Amgen, Janssen, and Boehringer Ingelheim. Dr. Latini and Dr. Masson have received grant support and travel reimbursements from Roche Diagnostics. Dr. Tavazzi reports personal fees from Servier, personal fees from CVIE Therapeutics, outside the submitted work. Dr. Gravning reports lecture fees from AstraZeneca, Siemens and Abbott Laboratories, outside the submitted work. Dr. Brunner-La Rocca reports unrestricted research grants and consulting fees from Roche Diagnostics, as well as unrestricted research grants from Novartis and Vifor outside this work. Dr. Bayes-Genis has received grant support from Roche Diagnosis, lecture honoraria from Roche Diagnostics and Critical Diagnostics, and consulting income from Roche Diagnostics, Critical Diagnostics, and Novartis. Dr. Lupón has received lecture honoraria from Roche Diagnostics. Dr. de Boer reports that Roche, Novartis, and AstraZeneca offered consultancy to UMCG; he also reports grants from AstraZeneca, grants from Bristol Myers Squibb, and grants from Trevena, outside the submitted work. Dr. Gustafsson reports personal fees from Boehringer-Ingelheim, personal fees from Novo Nordisk, personal fees from Novartis, personal fees from MSD, personal fees from Astra-Zeneca, outside the submitted work. Dr. Gaggin has received grant support from Roche and Portola; consulting income from Roche Diagnostics, Amgen and Ortho Clinical; research payments for clinical endpoint committees for EchoSense and Radiometer. Dr. Eggers has received honoraria from Abbott Laboratories and AstraZeneca, and has served as a consultant for Abbott Laboratories and Fiomi Diagnostics. Dr. Tang reports grants from National Institutes of Health, outside the submitted work. All disclosed relationships are modest. All other Authors have nothing to disclose.

Publisher Copyright:
© 2018 Elsevier B.V.

Keywords

Heart failure
Prognosis
Renal function
Troponin
Risk Assessment
Humans
Middle Aged
Male
Heart Failure/blood
Glomerular Filtration Rate/physiology
Aged, 80 and over
Biomarkers/blood
Female
Aged
Peptide Fragments/blood
Troponin T/blood
Chronic Disease
Natriuretic Peptide, Brain/blood

PubMed: MeSH publication types

Meta-Analysis
Journal Article

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10.1016/j.ijcard.2018.10.079

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Aimo, A., Januzzi, J. L., Vergaro, G., Ripoli, A., Latini, R., Masson, S., Magnoli, M., Anand, I. S., Cohn, J. N., Tavazzi, L., Tognoni, G., Gravning, J., Ueland, T., Nymo, S. H., Rocca, H. P. B. L., Bayes-Genis, A., Lupón, J., de Boer, R. A., Yoshihisa, A., ... Emdin, M. (2019). High-sensitivity troponin T, NT-proBNP and glomerular filtration rate: A multimarker strategy for risk stratification in chronic heart failure. International Journal of Cardiology, 277, 166-172. https://doi.org/10.1016/j.ijcard.2018.10.079

Aimo, A, Januzzi, JL, Vergaro, G, Ripoli, A, Latini, R, Masson, S, Magnoli, M, Anand, IS, Cohn, JN, Tavazzi, L, Tognoni, G, Gravning, J, Ueland, T, Nymo, SH, Rocca, HPBL, Bayes-Genis, A, Lupón, J, de Boer, RA, Yoshihisa, A, Takeishi, Y, Egstrup, M, Gustafsson, I, Gaggin, HK, Eggers, KM, Huber, K, Tentzeris, I, Wilson Tang, WH, Grodin, JL, Passino, C & Emdin, M 2019, 'High-sensitivity troponin T, NT-proBNP and glomerular filtration rate: A multimarker strategy for risk stratification in chronic heart failure', International Journal of Cardiology, vol. 277, pp. 166-172. https://doi.org/10.1016/j.ijcard.2018.10.079

@article{5f952a0bedec475eb56c5e15363b33c7,

title = "High-sensitivity troponin T, NT-proBNP and glomerular filtration rate: A multimarker strategy for risk stratification in chronic heart failure",

abstract = "BACKGROUND: In a recent individual patient data meta-analysis, high-sensitivity troponin T (hs-TnT) emerged as robust predictor of prognosis in stable chronic heart failure (HF). In the same population, we compared the relative predictive performances of hs-TnT, N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP), hs-C-reactive protein (hs-CRP), and estimated glomerular filtration rate (eGFR) for prognosis.METHODS AND RESULTS: 9289 patients (66 ± 12 years, 77% men, 85% LVEF <40%, 60% ischemic HF) were evaluated over a 2.4-year median follow-up. Median eGFR was 58 mL/min/1.73 m 2 (interquartile interval 46-70; n = 9220), hs-TnT 16 ng/L (8-20; n = 9289), NT-proBNP 1067 ng/L (433-2470; n = 8845), and hs-CRP 3.3 mg/L (1.4-7.8; n = 7083). In a model including all 3 biomarkers, only hs-TnT and NT-proBNP were independent predictors of all-cause and cardiovascular mortality and cardiovascular hospitalization. hs-TnT was a stronger predictor than NT-proBNP: for example, the risk for all-cause death increased by 54% per doubling of hs-TnT vs. 24% per doubling of NT-proBNP. eGFR showed independent prognostic value from both hs-TnT and NT-proBNP. The best hs-TnT and NT-proBNP cut-offs for the prediction of all-cause death increased progressively with declining renal function (eGFR ≥ 90: hs-TnT 13 ng/L and NT-proBNP 825 ng/L; eGFR < 30: hs-TnT 40 ng/L and NT-proBNP 4608 ng/L). Patient categorization according to these cut-offs effectively stratified patient prognosis across all eGFR classes. CONCLUSIONS: hs-TnT conveys independent prognostic information from NT-proBNP, while hs-CRP does not. Concomitant assessment of eGFR may further refine risk stratification. Patient classification according to hs-TnT and NT-proBNP cut-offs specific for the eGFR classes holds prognostic significance.",

keywords = "Heart failure, Prognosis, Renal function, Troponin, Risk Assessment, Humans, Middle Aged, Male, Heart Failure/blood, Glomerular Filtration Rate/physiology, Aged, 80 and over, Biomarkers/blood, Female, Aged, Peptide Fragments/blood, Troponin T/blood, Chronic Disease, Natriuretic Peptide, Brain/blood",

author = "Alberto Aimo and Januzzi, {James L.} and Giuseppe Vergaro and Andrea Ripoli and Roberto Latini and Serge Masson and Michela Magnoli and Anand, {Inder S.} and Cohn, {Jay N.} and Luigi Tavazzi and Gianni Tognoni and J{\o}rgen Gravning and Thor Ueland and Nymo, {St{\aa}le H.} and Rocca, {Hans Peter Brunner La} and Antoni Bayes-Genis and Josep Lup{\'o}n and {de Boer}, {Rudolf A.} and Akiomi Yoshihisa and Yasuchika Takeishi and Michael Egstrup and Ida Gustafsson and Gaggin, {Hanna K.} and Eggers, {Kai M.} and Kurt Huber and Ioannis Tentzeris and {Wilson Tang}, {W. H.} and Grodin, {Justin L.} and Claudio Passino and Michele Emdin",

note = "Funding Information: Dr. Januzzi has received grant support from Siemens, Singulex, and Prevencio; consulting income from Roche Diagnostics, Critical Diagnostics, Philips, and Novartis; and participates in clinical end point committees for Novartis, Amgen, Janssen, and Boehringer Ingelheim. Dr. Latini and Dr. Masson have received grant support and travel reimbursements from Roche Diagnostics. Dr. Tavazzi reports personal fees from Servier, personal fees from CVIE Therapeutics, outside the submitted work. Dr. Gravning reports lecture fees from AstraZeneca, Siemens and Abbott Laboratories, outside the submitted work. Dr. Brunner-La Rocca reports unrestricted research grants and consulting fees from Roche Diagnostics, as well as unrestricted research grants from Novartis and Vifor outside this work. Dr. Bayes-Genis has received grant support from Roche Diagnosis, lecture honoraria from Roche Diagnostics and Critical Diagnostics, and consulting income from Roche Diagnostics, Critical Diagnostics, and Novartis. Dr. Lup?n has received lecture honoraria from Roche Diagnostics. Dr. de Boer reports that Roche, Novartis, and AstraZeneca offered consultancy to UMCG; he also reports grants from AstraZeneca, grants from Bristol Myers Squibb, and grants from Trevena, outside the submitted work. Dr. Gustafsson reports personal fees from Boehringer-Ingelheim, personal fees from Novo Nordisk, personal fees from Novartis, personal fees from MSD, personal fees from Astra-Zeneca, outside the submitted work. Dr. Gaggin has received grant support from Roche and Portola; consulting income from Roche Diagnostics, Amgen and Ortho Clinical; research payments for clinical endpoint committees for EchoSense and Radiometer. Dr. Eggers has received honoraria from Abbott Laboratories and AstraZeneca, and has served as a consultant for Abbott Laboratories and Fiomi Diagnostics. Dr. Tang reports grants from National Institutes of Health, outside the submitted work. All disclosed relationships are modest. All other Authors have nothing to disclose. Funding Information: Dr. Januzzi has received grant support from Siemens , Singulex , and Prevencio ; consulting income from Roche Diagnostics, Critical Diagnostics, Philips, and Novartis; and participates in clinical end point committees for Novartis, Amgen, Janssen, and Boehringer Ingelheim. Dr. Latini and Dr. Masson have received grant support and travel reimbursements from Roche Diagnostics. Dr. Tavazzi reports personal fees from Servier, personal fees from CVIE Therapeutics, outside the submitted work. Dr. Gravning reports lecture fees from AstraZeneca, Siemens and Abbott Laboratories, outside the submitted work. Dr. Brunner-La Rocca reports unrestricted research grants and consulting fees from Roche Diagnostics, as well as unrestricted research grants from Novartis and Vifor outside this work. Dr. Bayes-Genis has received grant support from Roche Diagnosis, lecture honoraria from Roche Diagnostics and Critical Diagnostics, and consulting income from Roche Diagnostics, Critical Diagnostics, and Novartis. Dr. Lup{\'o}n has received lecture honoraria from Roche Diagnostics. Dr. de Boer reports that Roche, Novartis, and AstraZeneca offered consultancy to UMCG; he also reports grants from AstraZeneca, grants from Bristol Myers Squibb, and grants from Trevena, outside the submitted work. Dr. Gustafsson reports personal fees from Boehringer-Ingelheim, personal fees from Novo Nordisk, personal fees from Novartis, personal fees from MSD, personal fees from Astra-Zeneca, outside the submitted work. Dr. Gaggin has received grant support from Roche and Portola; consulting income from Roche Diagnostics, Amgen and Ortho Clinical; research payments for clinical endpoint committees for EchoSense and Radiometer. Dr. Eggers has received honoraria from Abbott Laboratories and AstraZeneca, and has served as a consultant for Abbott Laboratories and Fiomi Diagnostics. Dr. Tang reports grants from National Institutes of Health, outside the submitted work. All disclosed relationships are modest. All other Authors have nothing to disclose. Publisher Copyright: {\textcopyright} 2018 Elsevier B.V.",

year = "2019",

month = feb,

day = "15",

doi = "10.1016/j.ijcard.2018.10.079",

language = "English (US)",

volume = "277",

pages = "166--172",

journal = "International Journal of Cardiology",

issn = "0167-5273",

publisher = "Elsevier Ireland Ltd",

}

TY - JOUR

T1 - High-sensitivity troponin T, NT-proBNP and glomerular filtration rate

T2 - A multimarker strategy for risk stratification in chronic heart failure

AU - Aimo, Alberto

AU - Januzzi, James L.

AU - Vergaro, Giuseppe

AU - Ripoli, Andrea

AU - Latini, Roberto

AU - Masson, Serge

AU - Magnoli, Michela

AU - Anand, Inder S.

AU - Cohn, Jay N.

AU - Tavazzi, Luigi

AU - Tognoni, Gianni

AU - Gravning, Jørgen

AU - Ueland, Thor

AU - Nymo, Ståle H.

AU - Rocca, Hans Peter Brunner La

AU - Bayes-Genis, Antoni

AU - Lupón, Josep

AU - de Boer, Rudolf A.

AU - Yoshihisa, Akiomi

AU - Takeishi, Yasuchika

AU - Egstrup, Michael

AU - Gustafsson, Ida

AU - Gaggin, Hanna K.

AU - Eggers, Kai M.

AU - Huber, Kurt

AU - Tentzeris, Ioannis

AU - Wilson Tang, W. H.

AU - Grodin, Justin L.

AU - Passino, Claudio

AU - Emdin, Michele

N1 - Funding Information: Dr. Januzzi has received grant support from Siemens, Singulex, and Prevencio; consulting income from Roche Diagnostics, Critical Diagnostics, Philips, and Novartis; and participates in clinical end point committees for Novartis, Amgen, Janssen, and Boehringer Ingelheim. Dr. Latini and Dr. Masson have received grant support and travel reimbursements from Roche Diagnostics. Dr. Tavazzi reports personal fees from Servier, personal fees from CVIE Therapeutics, outside the submitted work. Dr. Gravning reports lecture fees from AstraZeneca, Siemens and Abbott Laboratories, outside the submitted work. Dr. Brunner-La Rocca reports unrestricted research grants and consulting fees from Roche Diagnostics, as well as unrestricted research grants from Novartis and Vifor outside this work. Dr. Bayes-Genis has received grant support from Roche Diagnosis, lecture honoraria from Roche Diagnostics and Critical Diagnostics, and consulting income from Roche Diagnostics, Critical Diagnostics, and Novartis. Dr. Lup?n has received lecture honoraria from Roche Diagnostics. Dr. de Boer reports that Roche, Novartis, and AstraZeneca offered consultancy to UMCG; he also reports grants from AstraZeneca, grants from Bristol Myers Squibb, and grants from Trevena, outside the submitted work. Dr. Gustafsson reports personal fees from Boehringer-Ingelheim, personal fees from Novo Nordisk, personal fees from Novartis, personal fees from MSD, personal fees from Astra-Zeneca, outside the submitted work. Dr. Gaggin has received grant support from Roche and Portola; consulting income from Roche Diagnostics, Amgen and Ortho Clinical; research payments for clinical endpoint committees for EchoSense and Radiometer. Dr. Eggers has received honoraria from Abbott Laboratories and AstraZeneca, and has served as a consultant for Abbott Laboratories and Fiomi Diagnostics. Dr. Tang reports grants from National Institutes of Health, outside the submitted work. All disclosed relationships are modest. All other Authors have nothing to disclose. Funding Information: Dr. Januzzi has received grant support from Siemens , Singulex , and Prevencio ; consulting income from Roche Diagnostics, Critical Diagnostics, Philips, and Novartis; and participates in clinical end point committees for Novartis, Amgen, Janssen, and Boehringer Ingelheim. Dr. Latini and Dr. Masson have received grant support and travel reimbursements from Roche Diagnostics. Dr. Tavazzi reports personal fees from Servier, personal fees from CVIE Therapeutics, outside the submitted work. Dr. Gravning reports lecture fees from AstraZeneca, Siemens and Abbott Laboratories, outside the submitted work. Dr. Brunner-La Rocca reports unrestricted research grants and consulting fees from Roche Diagnostics, as well as unrestricted research grants from Novartis and Vifor outside this work. Dr. Bayes-Genis has received grant support from Roche Diagnosis, lecture honoraria from Roche Diagnostics and Critical Diagnostics, and consulting income from Roche Diagnostics, Critical Diagnostics, and Novartis. Dr. Lupón has received lecture honoraria from Roche Diagnostics. Dr. de Boer reports that Roche, Novartis, and AstraZeneca offered consultancy to UMCG; he also reports grants from AstraZeneca, grants from Bristol Myers Squibb, and grants from Trevena, outside the submitted work. Dr. Gustafsson reports personal fees from Boehringer-Ingelheim, personal fees from Novo Nordisk, personal fees from Novartis, personal fees from MSD, personal fees from Astra-Zeneca, outside the submitted work. Dr. Gaggin has received grant support from Roche and Portola; consulting income from Roche Diagnostics, Amgen and Ortho Clinical; research payments for clinical endpoint committees for EchoSense and Radiometer. Dr. Eggers has received honoraria from Abbott Laboratories and AstraZeneca, and has served as a consultant for Abbott Laboratories and Fiomi Diagnostics. Dr. Tang reports grants from National Institutes of Health, outside the submitted work. All disclosed relationships are modest. All other Authors have nothing to disclose. Publisher Copyright: © 2018 Elsevier B.V.

PY - 2019/2/15

Y1 - 2019/2/15

N2 - BACKGROUND: In a recent individual patient data meta-analysis, high-sensitivity troponin T (hs-TnT) emerged as robust predictor of prognosis in stable chronic heart failure (HF). In the same population, we compared the relative predictive performances of hs-TnT, N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP), hs-C-reactive protein (hs-CRP), and estimated glomerular filtration rate (eGFR) for prognosis.METHODS AND RESULTS: 9289 patients (66 ± 12 years, 77% men, 85% LVEF <40%, 60% ischemic HF) were evaluated over a 2.4-year median follow-up. Median eGFR was 58 mL/min/1.73 m 2 (interquartile interval 46-70; n = 9220), hs-TnT 16 ng/L (8-20; n = 9289), NT-proBNP 1067 ng/L (433-2470; n = 8845), and hs-CRP 3.3 mg/L (1.4-7.8; n = 7083). In a model including all 3 biomarkers, only hs-TnT and NT-proBNP were independent predictors of all-cause and cardiovascular mortality and cardiovascular hospitalization. hs-TnT was a stronger predictor than NT-proBNP: for example, the risk for all-cause death increased by 54% per doubling of hs-TnT vs. 24% per doubling of NT-proBNP. eGFR showed independent prognostic value from both hs-TnT and NT-proBNP. The best hs-TnT and NT-proBNP cut-offs for the prediction of all-cause death increased progressively with declining renal function (eGFR ≥ 90: hs-TnT 13 ng/L and NT-proBNP 825 ng/L; eGFR < 30: hs-TnT 40 ng/L and NT-proBNP 4608 ng/L). Patient categorization according to these cut-offs effectively stratified patient prognosis across all eGFR classes. CONCLUSIONS: hs-TnT conveys independent prognostic information from NT-proBNP, while hs-CRP does not. Concomitant assessment of eGFR may further refine risk stratification. Patient classification according to hs-TnT and NT-proBNP cut-offs specific for the eGFR classes holds prognostic significance.

AB - BACKGROUND: In a recent individual patient data meta-analysis, high-sensitivity troponin T (hs-TnT) emerged as robust predictor of prognosis in stable chronic heart failure (HF). In the same population, we compared the relative predictive performances of hs-TnT, N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP), hs-C-reactive protein (hs-CRP), and estimated glomerular filtration rate (eGFR) for prognosis.METHODS AND RESULTS: 9289 patients (66 ± 12 years, 77% men, 85% LVEF <40%, 60% ischemic HF) were evaluated over a 2.4-year median follow-up. Median eGFR was 58 mL/min/1.73 m 2 (interquartile interval 46-70; n = 9220), hs-TnT 16 ng/L (8-20; n = 9289), NT-proBNP 1067 ng/L (433-2470; n = 8845), and hs-CRP 3.3 mg/L (1.4-7.8; n = 7083). In a model including all 3 biomarkers, only hs-TnT and NT-proBNP were independent predictors of all-cause and cardiovascular mortality and cardiovascular hospitalization. hs-TnT was a stronger predictor than NT-proBNP: for example, the risk for all-cause death increased by 54% per doubling of hs-TnT vs. 24% per doubling of NT-proBNP. eGFR showed independent prognostic value from both hs-TnT and NT-proBNP. The best hs-TnT and NT-proBNP cut-offs for the prediction of all-cause death increased progressively with declining renal function (eGFR ≥ 90: hs-TnT 13 ng/L and NT-proBNP 825 ng/L; eGFR < 30: hs-TnT 40 ng/L and NT-proBNP 4608 ng/L). Patient categorization according to these cut-offs effectively stratified patient prognosis across all eGFR classes. CONCLUSIONS: hs-TnT conveys independent prognostic information from NT-proBNP, while hs-CRP does not. Concomitant assessment of eGFR may further refine risk stratification. Patient classification according to hs-TnT and NT-proBNP cut-offs specific for the eGFR classes holds prognostic significance.

KW - Heart failure

KW - Prognosis

KW - Renal function

KW - Troponin

KW - Risk Assessment

KW - Humans

KW - Middle Aged

KW - Male

KW - Heart Failure/blood

KW - Glomerular Filtration Rate/physiology

KW - Aged, 80 and over

KW - Biomarkers/blood

KW - Female

KW - Aged

KW - Peptide Fragments/blood

KW - Troponin T/blood

KW - Chronic Disease

KW - Natriuretic Peptide, Brain/blood

UR - http://www.scopus.com/inward/record.url?scp=85056226093&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056226093&partnerID=8YFLogxK

U2 - 10.1016/j.ijcard.2018.10.079

DO - 10.1016/j.ijcard.2018.10.079

M3 - Article

C2 - 30416028

AN - SCOPUS:85056226093

SN - 0167-5273

VL - 277

SP - 166

EP - 172

JO - International Journal of Cardiology

JF - International Journal of Cardiology

ER -

High-sensitivity troponin T, NT-proBNP and glomerular filtration rate: A multimarker strategy for risk stratification in chronic heart failure

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